(20181217) Meysam Golmohammadi attended the International Conference on Machine Learning and Applications (ICMLA) and presented his paper on Deep Architectures for Spatio-Temporal Modeling.
(20181206) NEDC TUH EEG Artifact Corpus (v1.0.0): This is our first release of the TUH EEG Artifact Corpus. This corpus was developed to aid in EEG event classification such as seizure detection algorithms.
(20181113) The Neural Engineering Data Consortium gave a presentation at the John Hopkins University HLT on EEG Event Classification Using Deep Learning.
NIH Cohort Retrieval
Electronic medical records (EMRs) collected at every hospital in the country collectively contain a staggering wealth of biomedical knowledge. This information is essential for conducting comparative effectiveness research. Uncovering clinical knowledge that enables comparative research is the primary goal of this project.
TUH EEG Corpus
Electroencephalography (EEG) is the recording of electrical activity along the scalp using an array of electrodes positioned strategically around a patient's head. The TUH EEG Corpus represents NEDC's first effort to provide a massive corpus available to the community.